Articles, conference papers and other publications by Adam Misiorek
Statistical Tools for Finance and Insurance, 2011
Handbook of Computational Statistics, 2011
ABSTRACT The essence of the Value-at-Risk (VaR) and Expected Shortfall (ES) computations is estim... more ABSTRACT The essence of the Value-at-Risk (VaR) and Expected Shortfall (ES) computations is estimation of low quantiles in the portfolio return distributions. Hence, the performance of market risk measurement methods depends on the quality of distributional assumptions on the underlying risk factors. This chapter is intended as a guide to heavy-tailed models for VaR-type calculations. We first describe stable laws and their lighter-tailed generalizations, the so-called truncated and tempered stable distributions. Next we study the class of generalized hyperbolic laws, which – like tempered stable distributions – can be classified somewhere between infinite variance stable laws and the Gaussian distribution. Then we discuss copulas, which enable us to construct a multivariate distribution function from the marginal (possibly different) distribution functions of n individual asset returns in a way that takes their dependence structure into account. This dependence structure may be no longer measured by correlation, but by other adequate functions like rank correlation, comonotonicity or tail dependence. Finally, we provide numerical examples.
International Journal of Forecasting, Feb 1, 2008
Hsc Research Reports, 2006
ABSTRACT In this paper we assess the short-term forecasting power of different time series models... more ABSTRACT In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. However, instead of evaluating point predictions we concentrate on interval forecasts. The latter are specifically important for risk management purposes where one is more interested in predicting intervals for future price movements than simply point estimates. We find evidence that non-linear regime-switching models outperform their linear counterparts and that an additional GARCH component significantly improves interval forecasts of linear time series models.
Papers by Adam Misiorek
This empirical paper is a continuation of our earlier work on time series forecasting of day-ahea... more This empirical paper is a continuation of our earlier work on time series forecasting of day-ahead electricity prices. Given the controversy in the literature whether to use one large model across all hours or 24 separate models, we study if the model structure (and not only the coefficients) should change for different periods of the day. We find that leaving out the statistically insignificant factors leads to, on average, better point forecasts.
Hsc Software, Nov 5, 2007
MFE Toolbox accompanies the monograph "Modeling and Forecasting Electricity Loads and Pr... more MFE Toolbox accompanies the monograph "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach" by Rafal Weron, published by John Wiley and Sons, 2006. The toolbox consists of 58 functions, scripts and data files. Many functions include internally used routines, hence, the total number of functions is much larger. The files are grouped into seven categories: 1.Time series, 2.Distributions,
Przegląd Elektrotechniczny, 2006
In this paper we assess the short-term forecasting power of different time series models in the N... more In this paper we assess the short-term forecasting power of different time series models in the Nord Pool electricity spot market. We evaluate the accuracy of both point and interval predictions; the latter are specifically important for risk management purposes where one is more interested in predicting intervals for future price movements than simply point estimates. We find evidence that non-linear regime-switching models outperform their linear counterparts and that the interval forecasts of all models are overestimated in the relatively non-volatile periods.
We investigate the forecasting power of different time series models for electricity spot prices.... more We investigate the forecasting power of different time series models for electricity spot prices. The models include different specifications of linear autoregressive time series with heteroscedastic noise and/or additional fundamental variables and non-linear regime-switching TAR-type models. The models are tested on a time series of hourly system prices and loads from the California power market. Data from the period July 5, 1999 - April 2, 2000 are used for calibration and from the period April 3 - December 3, 2000 for out-of-sample testing.
Statistical Tools for Finance and Insurance, 2005
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Articles, conference papers and other publications by Adam Misiorek
Papers by Adam Misiorek